In Memory Data Grids, Demystified!

There is increased interest in using Kubernetes, the open-source container orchestration system for modern, stateful Big Data analytics workloads. The promised land is a unified platform that can handle cloud native stateless and stateful Big Data applications. However, stateful, multi-service Big Data cluster orchestration brings unique challenges. This session will delve into the technical gaps and considerations for Big Data on Kubernetes. Containers offer significant value to businesses; including increased developer agility, and the ability to move applications between on-premises servers, cloud instances, and across data centers. Organizations have embarked on this journey to containerization with an emphasis on stateless workloads. Stateless applications are usually microservices or containerized applications that don’t “store” data. Web services (such as front end UIs and simple, content-centric experiences) are often great candidates as stateless applications since HTTP is stateless by nature. There is no dependency on the local container storage for the stateless workload. Stateful applications, on the other hand, are services that require backing storage and keeping state is critical to running the service. Hadoop, Spark and to lesser extent, noSQL platforms such as Cassandra, MongoDB, Postgres, and mySQL are great examples. They require some form of persistent storage that will survive service restarts... Speakers Anant Chintamaneni, VP Products, BlueData Nanda Vijaydev, Director Solutions, BlueData

The principles and foundations of in memory data grids

Technologie Business

Uri Cohen
Head of Product @ GigaSpaces
@uri1803
github.com/uric
In-Memory Data Grids,
Demystified

Agenda
• Why IMDG?
• Brief History
• How It Works
– Data model & placement
– HA and fault tolerance
– Consistency
– Internals

Why
IMDG?
Today, more than
ever, there are many
choices when it
comes to storing your
data

® Copyright 2011 Gigaspaces Ltd. All Rights
Reserved
4
But There
Many
Solutions

Just A Few Years Back
® Copyright 2011 Gigaspaces Ltd. All Rights
Reserved
5

Memory will
always be faster
than disk
(usually by
orders of
magnitude)

67%
The ratio of IT
managers that think
that real time
analysis is the
biggest challenge
for
big data
implementations

40%
• Plan to use in
memory
technologies for
big data projects.
• Only 32%
mentioned
Hadoop

Hell, Even Gartner Thinks So
“In memory computing (IMC) … provides
transformational opportunities. The execution of
certain-types of hours-long batch processes can be
squeezed into minutes or even seconds …
Millions of events can be scanned in a matter of a few
tens of millisecond to detect correlations and patterns
pointing at emerging opportunities and threats "as
things happen.”

And
nowadays
HW and SW
just makes it
a whole lot
cheaper

Fast,
Transactional
Data Access
• Inventory
management
• Financial
reference data
• Real time
transactional data

Real Time
Stream
Processing
• Fraud Detection
• Click Stream
Analysis
• Real time
analytics
• Continuous
calculation

Heavyweight
Offline
Calculations
• Trade
Reconciliation
• Pattern analysis
and detection
• Number crunching

Caching
• Database
offloading
• Content heavy
websites

First There Were Local Caches
Cache
In process caching
of Key->Value data
structure
Distribute Cache
Partitioned cache
nodes
IMDG
Partitioned system
of record
IMDG.next()
Good for repetitive-data reads
Limited in capacity
Doesn’t handle write-heavy scenarios
Reads are only part latency path

Then Came Distributed Caches
Cache
In process caching
of Key->Value data
structure
Distribute Cache
Partitioned cache
nodes
IMDG
Partitioned system
of record
Increased Capacity
Still no support for write-heavy scenarios
Limited to ID-based reads
Reads are only part latency path
IMDG.next()

In Memory Data Grids
Cache
In process caching
of Key->Value data
structure
Increased capacity
Write scalability
Can serve as system of record with querying & transaction
semantics
Still limited in capacity
Latency can come from other parts of your app
Distribute Cache
Partitioned cache
nodes
IMDG
Partitioned system
of record
IMDG.next()

Data Placement – Fixed Hashing
27
hash(key) % #nodes

Fixed Hashing - HA
28
hash(key) % #nodes

Fixed Hashing – Scaling
29
Source: http://www.griddynamics.com/distributed-algorithms-in-nosql-databases/

Data Placement – Consistent Hashing
30
Source: http://www.griddynamics.com/distributed-algorithms-in-nosql-databases/

Data Placement – Consistent Hashing
31
Source: http://www.griddynamics.com/distributed-algorithms-in-nosql-databases/

Data Placement – Consistent Hashing
32
Source: http://www.griddynamics.com/distributed-algorithms-in-nosql-databases/

Data Placement – Consistent Hashing
33
Source: http://www.griddynamics.com/distributed-algorithms-in-nosql-databases/

Data Placement – Consistent Hashing
34
Source: http://www.griddynamics.com/distributed-algorithms-in-nosql-databases/

Data
Consistency
Since we’re dealing
with distributed
data, consistency
cannot be taken for
granted
• Read after write
• Read after read
• Write-write consistency

Some More Concerns
• Transactions
• Querying
• Failure detection
• Leader election
• Persistency
• Interoperability

IMDG.next()
Using IMDG for
messaging, BL

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Accelerating FinTech Innovation: Unleashing API Economy and GenAI Vasa Krishnan, Chief Technology Officer - FinResults Apidays New York 2024: The API Economy in the AI Era (April 30 & May 1, 2024) ------ Check out our conferences at https://www.apidays.global/ Do you want to sponsor or talk at one of our conferences? https://apidays.typeform.com/to/ILJeAaV8 Learn more on APIscene, the global media made by the community for the community: https://www.apiscene.io Explore the API ecosystem with the API Landscape: https://apilandscape.apiscene.io/

Apidays New York 2024 - Accelerating FinTech Innovation by Vasa Krishnan, Fin...

Passkeys: Developing APIs to enable passwordless authentication Cody Salas, Sr Developer Advocate | Solutions Architect - Yubico Apidays New York 2024: The API Economy in the AI Era (April 30 & May 1, 2024) ------ Check out our conferences at https://www.apidays.global/ Do you want to sponsor or talk at one of our conferences? https://apidays.typeform.com/to/ILJeAaV8 Learn more on APIscene, the global media made by the community for the community: https://www.apiscene.io Explore the API ecosystem with the API Landscape: https://apilandscape.apiscene.io/

Apidays New York 2024 - Passkeys: Developing APIs to enable passwordless auth...

Angeliki Cooney has spent over twenty years at the forefront of the life sciences industry, working out of Wynantskill, NY. She is highly regarded for her dedication to advancing the development and accessibility of innovative treatments for chronic diseases, rare disorders, and cancer. Her professional journey has centered on strategic consulting for biopharmaceutical companies, facilitating digital transformation, enhancing omnichannel engagement, and refining strategic commercial practices. Angeliki's innovative contributions include pioneering several software-as-a-service (SaaS) products for the life sciences sector, earning her three patents. As the Senior Vice President of Life Sciences at Avenga, Angeliki orchestrated the firm's strategic entry into the U.S. market. Avenga, a renowned digital engineering and consulting firm, partners with significant entities in the pharmaceutical and biotechnology fields. Her leadership was instrumental in expanding Avenga's client base and establishing its presence in the competitive U.S. market.

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Angeliki Cooney

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In this keynote, Asanka Abeysinghe, CTO,WSO2 will explore the shift towards platformless technology ecosystems and their importance in driving digital adaptability and innovation. We will discuss strategies for leveraging decentralized architectures and integrating diverse technologies, with a focus on building resilient, flexible, and future-ready IT infrastructures. We will also highlight WSO2's roadmap, emphasizing our commitment to supporting this transformative journey with our evolving product suite.

Platformless Horizons for Digital Adaptability

WSO2

Tracing the root cause of a performance issue requires a lot of patience, experience, and focus. It’s so hard that we sometimes attempt to guess by trying out tentative fixes, but that usually results in frustration, messy code, and a considerable waste of time and money. This talk explains how to correctly zoom in on a performance bottleneck using three levels of profiling: distributed tracing, metrics, and method profiling. After we learn to read the JVM profiler output as a flame graph, we explore a series of bottlenecks typical for backend systems, like connection/thread pool starvation, invisible aspects, blocking code, hot CPU methods, lock contention, and Virtual Thread pinning, and we learn to trace them even if they occur in library code you are not familiar with. Attend this talk and prepare for the performance issues that will eventually hit any successful system. About authorWith two decades of experience, Victor is a Java Champion working as a trainer for top companies in Europe. Five thousands developers in 120 companies attended his workshops, so he gets to debate every week the challenges that various projects struggle with. In return, Victor summarizes key points from these workshops in conference talks and online meetups for the European Software Crafters, the world’s largest developer community around architecture, refactoring, and testing. Discover how Victor can help you on victorrentea.ro : company training catalog, consultancy and YouTube playlists.

Finding Java's Hidden Performance Traps @ DevoxxUK 2024

Victor Rentea

Six Myths about Ontologies: The Basics of Formal Ontology

johnbeverley2021

Keynote 2: APIs in 2030: The Risk of Technological Sleepwalk Paolo Malinverno, Growth Advisor - The Business of Technology Apidays New York 2024: The API Economy in the AI Era (April 30 & May 1, 2024) ------ Check out our conferences at https://www.apidays.global/ Do you want to sponsor or talk at one of our conferences? https://apidays.typeform.com/to/ILJeAaV8 Learn more on APIscene, the global media made by the community for the community: https://www.apiscene.io Explore the API ecosystem with the API Landscape: https://apilandscape.apiscene.io/

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